A new key frame representation for video segment retrieval
In this paper, we propose an optimal key frame representation scheme based on global statistics for video shot retrieval. Each pixel in this optimal key frame is constructed by considering the probability of occurrence of those pixels at the corresponding pixel position among the frames in a video s...
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Published in | IEEE transactions on circuits and systems for video technology Vol. 15; no. 9; pp. 1148 - 1155 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York, NY
IEEE
01.09.2005
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | In this paper, we propose an optimal key frame representation scheme based on global statistics for video shot retrieval. Each pixel in this optimal key frame is constructed by considering the probability of occurrence of those pixels at the corresponding pixel position among the frames in a video shot. Therefore, this constructed key frame is called temporally maximum occurrence frame (TMOF), which is an optimal representation of all the frames in a video shot. The retrieval performance of this representation scheme is further improved by considering the k pixel values with the largest probabilities of occurrence and the highest peaks of the probability distribution of occurrence at each pixel position for a video shot. The corresponding schemes are called k-TMOF and k-pTMOF, respectively. These key frame representation schemes are compared to other histogram-based techniques for video shot representation and retrieval. In the experiments, three video sequences in the MPEG-7 content set were used to evaluate the performances of the different key frame representation schemes. Experimental results show that our proposed representations outperform the alpha-trimmed average histogram for video retrieval. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 |
ISSN: | 1051-8215 1558-2205 |
DOI: | 10.1109/TCSVT.2005.852623 |